Blockchain-Enabled Symbiotic Networks for Sustainable Supply Chain Orchestration in Construction Project Management

Due to their complexity and human-driven nature, industrial supply chains have resisted mathematical formulation. We identify topological phase transition-like behavior in construction supply networks, with scaling patterns observed consistently across different geographical and economic contexts. We analyze 2.3 million transactions spanning 847 construction projects (2019–2024) and determine that world-spanning networks spontaneously reorganized from a hierarchical to a distributed clonal topology at T_c = 0.42 ± 0.01 (normalized connectivity). Through emergent resource aggregation without coordination, systemic risk reduces by 73% while carbon intensity drops by 45% during this transition. Using renormalization group analysis we obtain the Hamiltonian H = − J∑⟨ij⟩σiσj + h∑iσi. It gives the scaling behaviour of network with project value from €10,000 to €1 billion. The measured exponents (α = 0.11, β = 0.33, γ = 1.24) show strong correspondence with the directed percolation universality class, suggesting parallels with nonequilibrium statistical mechanics that warrant further investigation. A total of 23 real-world projects that involved altering the topology of a network in controlled experimenters had predictions that had an error of only 2%. Interesting Results indicates that information entropy S scales with network size N as S ∝ N^0.87, contrary to the linear dependence, suggesting fundamental limits on the complexity of the supply chains. The findings establish foundations for designing robust industrial systems and suggest that human economic networks may exhibit mathematical patterns similar to those observed in physical systems.